Performance Assessment of a Variable-Rate Fertilizer Applicator

Abstract

The objective of this study was to test the performance of a Field-IQ sprayer control system which was interfaced with a John Deere liquid fertilizer applicator. The sprayer control system includes Case IH FM-1000 display integrated with DGPS, Field-IQ spray control with full harness, flowmeter and auto-range valve, and the pump. Tap water was used to simulate the UAN 32% nitrogen fertilizer solution in the test. A total of 120 samples from 8 rows of the applicator in 5 application rates (34, 67, 101, 135, and 168 kg/ha) were collected, and the data were analyzed for application uniformity and application rate accuracy of the system. Results showed the greatest variation from the application rate baseline among the rows was 10.1% and occurred at a swath-end row with the lowest application rate of 34 kg/ha. The rows in the middle section of the swath had the lower variation than the rows at the two swath-ends. The application uniformity increased as the application rate increased. The absolute error of application rate ranged from 1.3% to 6.5% with an average of 3.76%. There was no significant difference between the selected application rate and actual application rate (p > 0.8686).

Single-Neuron PID UAV Variable Fertilizer Application Control System Based on a Weighted Coefficient Learning Correction

“…Thus, aerial variable fertilizer application technology is highly efficient for fertilizer application. Additionally, aerial application allows for more stable plant growth, and also decreases the environmental pollution caused by the less well-controlled application of nutrients by traditional fertilizer application technology [18,19]. Compared with other closed-canopy crops, rice has a weak root system during the early stage of growth.…”

Variable rate fertilizer application technology for nutrient management: A review

“…The maize variable fertilisation model is the establishment of nitrogen, phosphorus, and potassium levels based on a predetermined sampling point plot. The GPS based VRFA system was developed by Chandel et al [63] . The prescription map (Grid size 8 m×8 m) was created using Arc GIS software.…”

“…Consequently, the cornerstone of implementing precision agriculture (PA) techniques lies in dividing agricultural areas into multiple MZs based on factors such as soil mapping, crop growth, and yield [22,23] . Moreover, these systems offer the advantage of improving the efficiency of agricultural inputs by lowering costs and mitigating environmental pollution [24][25][26] . The sensor and map based approach are two basic techniques for adopting site specific management for variable rate input applications [27,28] .…”